Below you can find a selection of the CCS members' current research projects. Follow the links for more details, demos and related papers.

The Adaptive Mind

The Cluster of Excellence “The Adaptive Mind” aims to measure and model how people see, think and act adaptively in open-ended conditions, and study the consequences for mental health when adaptive processes fail. This will not only transform our scientific understanding of how the mind works, but also help develop safe, robust and human-aligned AI and robotics systems.
Ongoing research funded by the German Federal Government and the individual Federal States, Funding Agency: German Research Foundation.

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RAI – Reasonable Artificial Intelligence

The Cluster of Excellence “RAI – Reasonable Artificial Intelligence” aims to develop a new generation of AI called Reasonable Artificial Intelligence (RAI). This new form of AI will learn in more reasonable ways, with models being trained in a decentralized fashion, continuously improving over time, building an abstract knowledge of the world, and with an innate ability to reason, interact, and adapt to their surroundings.
Ongoing research funded by the German Federal Government and the individual Federal States, Funding Agency: German Research Foundation.

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C4: Compositional Compression in Cognition and Culture

While the concept of compositionality describes the human ability to solve new problems by recombining familiar elements in novel ways, cumulative culture refers to the capacity to build on the knowledge of previous generations. Both features have been proposed separately as unique characteristics of human intelligence, distinguishing it from other animal cognition and from AI. The funded project aims to unite these two core concepts in a single mathematical framework.

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SEGMENT – 3D scene understanding in two glances

In project "SEGMENT", Professor Thomas Wallis and his team are investigating what is known as visual segmentation. This is when the human brain attempts to recognise which parts of a scene shown, for instance, in a photo belong to which objects. The researchers want to find out how people combine information from active 3D vision, and how they can learn this combination from visual experiences.

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ACTOR – Towards a computational account of natural sequential behavior

The European Research Council is funding the project "ACTOR – Towards a computational account of natural sequential behaviour" over a period of five years. The aim of the project is to gain a better understanding of human behaviour in everyday tasks by means of cognitive computational models, i.e. by applying algorithms similar to artificial intelligence. ACTOR has been awarded as an “ERC Consolidator Grant" to Constantin Rothkopf.

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WhiteBox – explainable models for human and artificial intelligence

The LOEWE Research Cluster “WhiteBox – explainable models for human and artificial intelligence” is aimed at developing methods at the intersection between Cognitive Science and AI to make human and artificial intelligence more understandable.
Ongoing research funded by Hessen State Ministry for Higher Education, Research and the Arts.

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LokoAssist

LokoAssist aims at a “seamless” integration of assistive devices into the human body schema. This requires an automatic recognition of different movement intentions to create and intuitive and predictable motor behavior. Such assistance systems promise a significantly expanded range of motion with lower metabolic energy expenditure, better individual adaptability, and greater ease of movement.
Ongoing research funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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RED – Robust, Explainable Deep Networks in Computer Vision

The goal of his project is to develop methods that make artificial neural networks in computer vision, particularly so-called deep networks, more robust and more explainable. One particular aim is to increase user trust in machine learning approaches to computer vision, for example in the context of autonomous vehicles.

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You can also view our former projects here